import warnings
from dataclasses import dataclass
from typing import List, Dict

from openpyxl import load_workbook
import requests
import json

from model.consts import BASE_URL, HEADERS, EXCEL_FILE_PATH
from model.excel_utils import process_merged_cells
from model.json_utils import default_encoder
from model.model_def import LineStatistics, StructField, Struct

warnings.filterwarnings("ignore", category=UserWarning)


def parse_data_struct(workbook, sheet_index) -> Dict[str, List[StructField]]:
    """
    解析数据结构函数
    从指定的Excel文件中读取数据，并将数据结构映射存放在一个字典中。
    返回值:
        data_struct_map (dict): 数据结构映射的字典，将数据结构名称作为键，对应的值为数据字段键的列表
    """
    # 打开 Excel 文件
    # 风险模型表单
    sheet = workbook.worksheets[sheet_index]
    merged_cells = process_merged_cells(sheet)
    data_struct_map: Dict[str, List[StructField]] = {}
    # 行统计信息，用于调试数据缺失
    line_statistics = LineStatistics()
    # 读取数据
    for row_number, row in enumerate(sheet.iter_rows(), start=1):
        line_statistics.total += 1
        # row,col 和  row[index] 中的index 下标不同，index 0开始, merged_cells 中 1开始
        struct_name, field_name, field_key = (
            row[5].value if row[5].value is not None else merged_cells.get((row_number, 6)),
            row[6].value if row[6].value is not None else merged_cells.get((row_number, 7)),
            row[7].value if row[7].value is not None else merged_cells.get((row_number, 8)))
        if not (struct_name and field_name and field_key):
            line_statistics.fail += 1
            print(f"failed data {row_number}: {struct_name} {field_name} {field_key}")
            continue
        struct_name = struct_name.replace('\n', '')
        if struct_name in data_struct_map:
            data_struct_map[struct_name].append(StructField(field_name, field_key))
        else:
            data_struct_map[struct_name] = [StructField(field_name, field_key)]
        line_statistics.success += 1
    print(data_struct_map)
    print(f'line statistics: {line_statistics}')
    return data_struct_map


def save_data_structs(data_struct_map):
    for struct_name, fields in data_struct_map.items():
        struct = Struct()
        struct.name, struct.key, struct.remark = struct_name, struct_name, struct_name
        processed_field_keys = set()
        for field in fields:
            if field.field_key in processed_field_keys:
                continue
            struct_field = {
                'key': field.field_key,
                'name': field.field_name,
                'type': 2,
                'remark': field.field_name
            }
            if struct.fields is None:
                struct.fields = [struct_field]
            else:
                struct.fields.append(struct_field)
            processed_field_keys.add(field.field_key)
        json_body = json.dumps(struct, default=default_encoder)
        print(f'fields count : {len(struct.fields)}  req: {json_body}')
        resp = requests.post(
            url=BASE_URL + '/risk/sky/struct',
            data=json_body,
            headers=HEADERS
        )
        print('resp: ', resp.json())


def main():
    # 解析
    workbook = load_workbook(filename=EXCEL_FILE_PATH)
    length = 2  # len(workbook.worksheets)
    for sheet_index in range(length):
        struct_fields_map = parse_data_struct(workbook, sheet_index)
        save_data_structs(struct_fields_map)


if __name__ == '__main__':
    main()